Question 830 of 1,711
Redshift Distribution Key Optimization
A data engineering team uses Amazon Redshift for analytics. They notice that queries on a large fact table are slow. The table is distributed using DISTSTYLE ALL. Which design change would most likely improve query performance?
Quick Answer
The answer is to change DISTSTYLE from ALL to KEY on a column used in frequent joins. This is correct because DISTSTYLE ALL copies the entire large fact table to every node, wasting storage and creating network bottlenecks during both data loading and query execution, whereas DISTSTYLE KEY collocates related rows from the fact and dimension tables on the same slice based on the join key, eliminating the need for costly data redistribution or broadcasting across the network. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of Redshift distribution key optimization and how table design directly impacts query performance—a common trap is assuming ALL style is always faster for joins, but it backfires on large tables due to excessive data movement. Remember the memory tip: “ALL is small, KEY is for joins”—use ALL only for tiny dimension tables, and always choose a high-cardinality join column as your distribution key for large fact tables.
⚠ Common exam trap
Test-takers frequently assume adding a SORTKEY (Option C) is the universal performance fix, but for large fact tables the dominant bottleneck is data distribution and join collocation, not scan efficiency.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Change DISTSTYLE to KEY on a column used in frequent joins.
DISTSTYLE ALL copies the entire table to every node, which is inefficient for large fact tables because it wastes storage and network bandwidth during data loading and query execution. Changing to DISTSTYLE KEY on a column used in frequent joins collocates related rows on the same slice, reducing the need to broadcast or redistribute data across the network during joins, which directly improves query performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change DISTSTYLE to EVEN to distribute rows evenly across slices.
Why it's wrong here
EVEN distribution can cause broadcast joins and degrade performance.
- ✗
Increase the number of nodes in the Redshift cluster.
Why it's wrong here
Adding nodes is a scaling solution but does not fix the distribution design issue.
- ✗
Change the table to use a SORTKEY on the most frequently filtered column.
Why it's wrong here
SORTKEY improves range scans but does not address distribution overhead.
- ✓
Change DISTSTYLE to KEY on a column used in frequent joins.
Why this is correct
KEY distribution collocates rows on the same node, reducing data movement during joins.
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Same concept, more angles
4 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses Amazon Redshift for analytics. The data engineer notices that some queries are slow and the EXPLAIN plan shows a 'Seq Scan' on a large table. Which data store management action would most likely improve query performance?
medium- A.Run the ANALYZE command to update table statistics.
- B.Enable automatic compression on the table.
- ✓ C.Define appropriate sort keys and distribution styles.
- D.Run the VACUUM command to reclaim space.
Why C: A Seq Scan indicates that Redshift is scanning the entire table because it lacks efficient data organization. Defining appropriate sort keys and distribution styles organizes data on disk and across nodes, enabling Redshift to use zone maps to skip large portions of data and to execute parallel, co-located joins, which directly reduces the need for full table scans.
Variation 2. A company uses Amazon Redshift for analytics. The data engineer notices that queries are slow and the system is experiencing high disk usage. The engineer suspects that the distribution style is suboptimal. Which action should the engineer take to improve query performance?
hard- A.Convert all tables to use SORTKEY on the most frequently filtered column.
- B.Increase the number of nodes in the cluster to distribute data across more slices.
- ✓ C.Use the DISTSTYLE AUTO setting and analyze query patterns to let Redshift choose.
- D.Set all tables to DISTSTYLE EVEN to distribute data evenly.
Why C: DISTSTYLE AUTO allows Amazon Redshift to automatically assign distribution styles (KEY, EVEN, or ALL) based on query patterns and table size, optimizing data distribution for improved query performance. This is particularly effective when the engineer suspects suboptimal distribution but lacks detailed knowledge of the ideal key, as Redshift analyzes workload patterns to reduce data movement and disk usage.
Variation 3. A company uses Amazon Redshift for analytics. The data engineering team wants to improve query performance for frequently used aggregate queries. Which TWO actions would help achieve this?
medium- A.Increase the number of WLM query queues
- ✓ B.Use distribution keys to collocate data on the same node slices
- C.Run the VACUUM command to reclaim space from deleted rows
- ✓ D.Define appropriate sort keys on the tables
- E.Increase the number of nodes in the cluster
Why B: Distribution keys determine how data is distributed across node slices in Amazon Redshift. By choosing distribution keys that align with the join and aggregation columns, the database can collocate related data on the same slice, minimizing data movement during query execution. This directly improves performance for aggregate queries by reducing network traffic and enabling local computation.
Variation 4. A company uses Amazon Redshift for analytics. They notice that some queries are slow due to data redistribution. The data engineer wants to minimize data movement across nodes. Which table design strategy should be used? (Choose TWO.)
hard- A.Set the distribution style to AUTO for all tables.
- B.Define compound sort keys on frequently filtered columns.
- ✓ C.Choose a distribution key that matches the join key for large tables.
- D.Use EVEN distribution for all tables.
- ✓ E.Use distribution style ALL for small dimension tables.
Why C: When large tables are joined on their distribution keys, Redshift can perform a collocated join, meaning the matching rows are already on the same node slice, eliminating the need to redistribute data across the network. This directly minimizes data movement and speeds up query execution.
Last reviewed: Jun 11, 2026
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